NBA Early-Career Competition Analysis
  • Full Analysis
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  • Objective
  • Main Findings
  • Methods
  • Why It Matters
  • Deep Dive

NBA Early-Career Competition Analysis

Author

Dominique Morris

Objective

Examine how rookie- and sophomore-year positional competition affects NBA lottery picks’ scoring trajectories over their first five seasons. Positional competition measures how crowded a player’s role is on their team.


Main Findings

★ After accounting for individual and team-level factors, players facing higher sophomore-year competition start strong, then plateau or even decline in points per game over time, while rookie-year competition slightly boosts baseline scoring without affecting growth.


Methods

  • Data: Player stats from Basketball Reference, cleaned and processed in Python and R.

  • Model: Linear mixed-effects model capturing player-level differences over time.

  • Validation: Confidence intervals and diagnostics ensured reliable estimates.

  • Visualization: Interactive plots of predicted scoring trajectories.


Why It Matters

The methods used here can be applied beyond sports analytics, in areas such as:

  • Finance: Modeling portfolio growth under varying conditions.

  • Healthcare: Tracking patient outcomes over time under different treatments.

  • Education: Evaluating student performance trajectories across learning environments.


Deep Dive

The full analysis including data processing, model building, and detailed results is available:

Read the Full Analysis